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Biological Dark Matter (BDM). A main idea of this project is to make use of the pattern matching abilities of the Tsetlin Machine in machine learning to be able to recognize signals in the BDM in
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on leveraging deep learning and advanced image processing techniques to improve the current tools for biomonitoring of aquatic ecosystems. This position involves the development and application of machine
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application of machine learning algorithms to automatically classify freshwater benthic diatoms at the species level and quantify key morphological traits. These advancements aim to improve ecological
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related subject (or be close to completing the degree); demonstrated interest in AI reasoning systems, algorithms, IoT, context-aware pervasive computing, machine learning and data analysis, software
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optimizations and approaches inspired by machine learning within the framework of cognitive radar; and C) verify the developed approaches with suitable simulations and experimental demonstrations. Specifically
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» Programming Medical sciences » Other Researcher Profile First Stage Researcher (R1) Country Austria Application Deadline 9 Apr 2025 - 21:59 (UTC) Type of Contract Permanent Job Status Full-time Is the job
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economicssystems/ operations management, econometrics, machine learning, extensive data analytics and qualitative research methods. The student will collaborate closely with advisors to identify, develop, and carry